collaborators

10 papers

cs.AI2026

Tracing the Heart: An Evidence-Linked Pipeline for Heart-Failure Feature Engineering

Soorya Ram Shimgekar, Michelle Hu, Dorisa Shehi +10

Electronic health record (EHR) feature engineering is a major bottleneck in clinical research and AI, accounting for 39-45% of data scientists' workload. This is especially pronoun…

cs.AI2026

Trust but Verify:Evidence-Linked Multi-Agent Clinical Information Extraction in Pathology

Yufan Wang, Anit Kumar Sahu, Yan Fei Ng +8

Clinical feature extraction from pathology reports is challenging because relevant evidence may be distributed across coded and narrative fields and depend on specimen attribution,…

cs.CL2026

Toxic HallucinAItions: Perturbing Prompts and Tracing LLM Circuits

Soorya Ram Shimgekar, Agam Goyal, Amruta Parulekar +6

Large language models (LLMs) are increasingly deployed in conversational settings where user tone ranges from polite to adversarial or toxic, yet less is known about whether toxic…

cs.HC2026

LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback

Jiwon Kim, Maya Ajit, Sherry Gong +4

Large language models (LLMs) show promise in generating supportive responses for mental health queries, but improving their usefulness, empathy, and safety often requires substanti…

cs.HC2026

AI Psychosis: Does Conversational AI Amplify Delusion-Related Language?

Soorya Ram Shimgekar, Vipin Gunda, Jiwon Kim +3

Conversational AI systems are increasingly used for personal reflection and emotional disclosure, raising concerns about their effects on vulnerable users. Recent anecdotal reports…

cs.SI2026

Detecting Early and Implicit Suicidal Ideation via Longitudinal and Information Environment Signals on Social Media

Soorya Ram Shimgekar, Ruining Zhao, Agam Goyal +5

On social media, several individuals experiencing suicidal ideation (SI) do not disclose their distress explicitly. Instead, signs may surface indirectly through everyday posts or…